CRF-EfficientUNet: An Improved UNet Framework for Polyp Segmentation in Colonoscopy Images With Combined Asymmetric Loss Function and CRF-RNN Layer
Colonoscopy is considered the gold-standard investigation for colorectal cancer screening. However, the polyps miss rate in clinical practice is relatively high due to different factors. This presents an opportunity to use AI models to automatically detect and segment polyps, supporting clinicians t...
Enregistré dans:
| Auteurs principaux: | , , |
|---|---|
| Format: | article |
| Langue: | EN |
| Publié: |
IEEE
2021
|
| Sujets: | |
| Accès en ligne: | https://doaj.org/article/b8277e09f22b489a93e75b1ff6f8e24d |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|